Effects of the surface coupling strength in the WRF/Noah-MP model on regional climate simulations over China

Abstract

Land-atmosphere energy and moisture exchange can strongly influence local and regional climate. However, high uncertainty exits in the representation of landatmosphere interactions in numerical models. The parameterization of surface exchange process is greatly affected by varying the parameter Czil which, however, is typically set to a domain-wide constant value. In this study, we examine the sensitivity of regional climate simulations over China to different surface exchange strengths using three Czil schemes (default without Czil, constant Czil = 0.1, and dynamic canopy-heightdependent Czil-h schemes) in the 13-km-resolution Weather Research and Forecasting model coupled with a Noah land surface model with multi-parameterization options (WRF/Noah-MP). Our results demonstrate that the Czil-h scheme substantially reduces the overestimations of land-atmosphere coupling strength in the other two schemes, and comparisons with the ChinaFLUX observations indicate the capability of the Czilh scheme to better match the observed surface energy and water variations. The results of the Czil schemes applying to four typical climate zones of China present that the Czilh simulations are in the closest agreements with the field observations. The Czil-h scheme can narrow the positive discrepancies of simulated precipitation and surface fluxes as well as the negative biases of Ts in areas of Northeast, North China, EasternNorthwest, and Southwest. Especially, the above remarkable improvements produced by the Czil-h scheme are primarily over areas covering short vegetation. Also noted that the precipitation simulated by the Czil-h scheme exhibits more intricate and unclear changes compared with surface fluxes simulations due to the non-local impacts of surface exchange strength resulted from the fluidity of the atmosphere. Overall, our findings highlight the applicability of the dynamical Czil as a better physical alternative to treat the surface exchange process in atmosphere coupling models.

Sensitivity of Heavy Convective Precipitation Simulations to Changes in Land‐Atmosphere Exchange Processes Over China

“…Second, this study was conducted by selecting and modeling several heavy precipitation events. Although previous studies (Chen et al, 2019;Zhang et al, 2021Zhang et al, , 2022 using offline LSMs and coupled climate models have verified the ability of the dynamical scheme in improving surface fluxes and climate simulations, the great uncertainties still exist in the convection-permitting simulations due to the low predictability of heavy convective precipitation (Crook, 1996;Fritsch & Carbone, 2004;Meyer & Haerter, 2020). More experiments conducted in the future are helpful for supporting the findings in this study.…”

“…Although significant improvements in simulating surface fluxes through the dynamic canopy-height-dependent scheme have been demonstrated in previous studies (Chen & Zhang, 2009;Chen et al, 2019;Zhang et al, 2021), it is hard to determine whether the dynamic scheme could provide improvements to precipitation simulations due to the nonlocal impacts of varying land-atmosphere exchange efficiency under the conditions of atmospheric fluidity (Trier et al, 2004;Zhang et al, 2022;Zheng, Kumar, & Niyogi, 2015). In addition, the important role of land-atmosphere exchange processes in determining precipitation predictability on long time scales (e.g., seasonal) through such as the feedback between soil moisture and precipitation has been identified by recent modeling studies (Koster et al, 2004(Koster et al, , 2006Lo et al, 2021).…”

“…Currently commonly used numerical models for operational and research applications still adopt equivalent Z om and Z ot (i.e., C zil ∼ 0) or take C zil as a constant (usually C zil = 0.1, i.e., Z om /Z ot = 10) (Chen et al, 1997;Gomez et al, 2020;Stepanenko et al, 2020;Zheng et al, 2012). However, some studies have indicated that considering land cover conditions in the formulation of C zil or the ratio Z om /Z ot could significantly improve simulations (Chen & Zhang, 2009;Zhang et al, 2022;Zheng et al, 2012). For instance, Zheng et al (2012) applied the ratio Z om /Z ot associated with green vegetation fraction to the National Centers for Environmental Prediction operational Global Forecast System, and they found substantially reduced cold biases of daytime land surface temperature over the arid western continental United States.…”